一种融合相对有效性的两阶段理想点法
Two-Stage TOPSIS Based on Relative Efficiency
DOI: 10.12677/ORF.2017.74013, PDF, HTML, XML, 下载: 1,350  浏览: 4,322  科研立项经费支持
作者: 邓兰梅, 黄天民:西南交通大学,数学学院,四川成都
关键词: 多目标问题理想点法相对有效性Pareto最优解层次分析法变异系数法Multi-Objective Problem TOPSIS Relative Efficiency Pareto Optimal Solution Analytic Hierarchy Process Coefficient of Variation
摘要: 对于多目标优化与决策问题的求解,决策者需要在Pareto最优解集中挑选出一个最终的决策方案。本文提出了一种包含多目标优化与决策的两阶段理想点法,在第一阶段采用基于相对有效性的理想点法得到Pareto最优解集,决策过程中决策者参与和计算权重向量交互进行,保证了权重向量客观性和决策者的参与程度;在第二阶段中,采用基于层次分析法主观赋权和变异系数法客观赋权的线性组合赋权的理想点法对Pareto最优解进行排序,以帮助决策者完成决策。
Abstract: For solving multi-objective optimization and decision making problems, decision-makers need to pick out a final decision from the Pareto optimal solution set. A two-stage technique for order preference by similarity to ideal solution (TOPSIS) containing multi-objective optimization and decision is presented. In the first stage, Pareto optimal solution set is obtained by using the TOPSIS based on relative efficiency. Decision-makers’ participation interacts with calculating weight vector in decision-making process, ensuring the objectivity of the weight vector and the degree of decision-makers’ participation; in the second phase, sort of the Pareto optimal solutions is obtained by using TOPSIS based on the linear combination of subjective empowerment based on the analytic hierarchy process (AHP) and objective empowerment based on coefficient of variation, helping decision-makers complete the decision.
文章引用:邓兰梅, 黄天民. 一种融合相对有效性的两阶段理想点法[J]. 运筹与模糊学, 2017, 7(4): 110-137. https://doi.org/10.12677/ORF.2017.74013

参考文献

[1] 邱威, 张建华, 刘念. 电压稳定约束下最优潮流的多目标优化与决策[J]. 电力自动化设备, 2011, 31(5): 34-38.
[2] 胡翩. 船舶概念设计阶段的多目标优化与决策[J]. 计算机与数字工程, 2014, 42(3): 390-394.
[3] 孟小丁. 求解多目标优化问题的若干算法概述[J]. 信息通信, 2015(7): 8-9.
[4] 杨桂元, 郑亚豪. 多目标决策问题及其求解方法研究[J]. 数学的实践与认识, 2012, 42(2): 108-115.
[5] 张乐文, 邱道宏, 等. 基于粗糙集和理想点法的隧道围岩分类研究[J]. 岩土力学, 2011, 32(1): 171-175.
[6] Olson, D.L. (2004) Comparison of Weights in TOPSIS Models. Mathematical and Computer Modelling, 40, 721-727.
[7] 艾正海. 关于多目标决策问题的理想点法研究[D]: [硕士学位论文]. 成都: 西南交通大学, 2007.
[8] Wei, X., Zhang, B. and Wang, Q. (2014) Improved TOPSIS Model Based on Interval Numbers. WIT Transactions on Information and Communication Technologies, 48, 55-61.
[9] Elhassouny, A. and Smarandache, F. (2016) Neutrosophic-Simplified-TOPSIS Multi-Criteria Decision-Making using Combined Simplified-TOPSIS Method and Neutrosophics. IEEE International Conference on Fuzzy Systems, 2468-2474.
[10] Baky, A., Ibrahim, A.-S. and Mahmoud, A. (2013) TOPSIS for Bi-Level MODM Problems. Applied Mathematical Modelling, 37, 1004-1015.
[11] Jadidi, O., Firouzi, F. and Bagliery, E. (2010) TOPSIS Method for Supplier Selection Problem. World Academy of Science, Engineering and Technology, No. 47, 956-958.
[12] Yang, Y. (2010) SWOT-TOPSIS Integration Method for Strategic Decision. Proceedings of the International Conference on E-Business and E-Government, 1575-1578.
https://doi.org/10.1109/ICEE.2010.399
[13] Xu, J.H., Li, L., Liu, J.Y., Fu, C.Q. and Zheng, J.L. (2011) Imprecise DEA Model Based on TOPSIS. Applied Mechanics and Materials, 63-64, 723-727.
https://doi.org/10.4028/www.scientific.net/AMM.63-64.723
[14] Niu, D. and Lv, J. (2008) Application of Improved TOPSIS Method Based on ACO and BP Algorithm. Proceedings of the World Congress on Intelligent Control and Automation, 6183-6186.
[15] Athawale, V.M. and Chakraborty, S. (2010) A Combined Topsis-Ahp Method for Conveyor Belt Material Selection. Journal of the Institution of Engineers, Part PR: Production Engineering Division, 90, 8-13.
[16] 刘晓东, 等. 基于蒙特卡洛仿真的理想点决策方法及其应用[J]. 数学的实践与认识, 2005, 35(10): 99-103.
[17] 程芬, 等. 基于数据包络与逼近理想点法的预防性养护决策[J]. 交通科技与经济, 2016, 18(1): 56-60.
[18] 戎卫东, 杨新民. 向量优化及其若干进展[J]. 运筹学学报, 2014, 18(1): 9-38.
[19] 贺莉, 刘庆怀. 多目标优化理论与连续化方法[M]. 北京: 科学出版社, 2015.
[20] 冯俊文. 多目标优化与决策中的相对有效性理论[J]. 系统工程与电子技术, 1994(4): 38-43.
[21] 江正华. AHP中正互反判断矩阵一致性调整的新方法[J]. 南京大学学报数学半年刊, 2013, 30(2): 224-237.
[22] 吴祈宗, 等. 运筹学与最优化MATLAB编程[M]. 北京: 机械工业出版社, 2009.
[23] 王莲芬, 许树柏. 层次分析法引论[M]. 北京: 中国人民大学出版社, 1990.
[24] Wind, Y. and Saaty, T.L. (1980) Marketing Applications of the Analytic Hierarchy Process. Management Science, 26, 641-658.
https://doi.org/10.1287/mnsc.26.7.641
[25] 张炳江. 层次分析法及其应用案例[M]. 北京: 电子工业出版社, 2014.